Abstract
Abstract A recent analysis published in this journal found different relationships between mean Ellenberg indicator values and environmental measurements in different vegetation types. The cause was stated as bias in mean Ellenberg values between relevés which in turn suggested to reflect a bias in individual Ellenberg values. We discuss two phenomena that could explain these results without the need to invoke bias in either individual or mean Ellenberg values. Firstly, slopes of linear regression lines underestimate true relationships when analyses involve explanatory variables measured with error. Secondly, syntaxon‐specific distributions of Ellenberg values follow from the floristic definition of phytosociological units. Mean Ellenberg values per relevé therefore carry the stamp of their associated syntaxon even though associated abiotic conditions may vary between relevés. This will lead to variation in slopes and intercepts between vegetation types not because of bias in individual Ellenberg values but because of prescribed bias in the distribution of Ellenberg values between syntaxa. The residual variation in calibrations carried out across vegetation types is undoubtedly reduced by introducing vegetation type as a factor. However users should note that this is unlikely to reflect bias in individual Ellenberg values but is more likely to reflect error in environmental measurements as well the constraint imposed by phytosociological classification.
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Claims 5
Claim · model-written summary
Measurement error in explanatory variables causes regression slopes to underestimate true relationships.
Verbatim
e0“slopes of linear regression lines underestimate true relationships when analyses involve explanatory variables measured with error”
t0“vegetation”
Claim · model-written summary
Syntaxon-specific Ellenberg value distributions follow from floristic definitions.
Verbatim
e0“syntaxon‐specific distributions of Ellenberg values follow from the floristic definition of phytosociological units”
t0“vegetation”
Claim · model-written summary
Mean Ellenberg values retain a syntaxon imprint despite variation in abiotic conditions.
Verbatim
e0“Mean Ellenberg values per relevé therefore carry the stamp of their associated syntaxon even though associated abiotic conditions may vary between relevés.”
t0“vegetation”
Claim · model-written summary
Vegetation types vary in calibration slopes and intercepts because Ellenberg values are distributed differently among syntaxa.
Verbatim
e0“This will lead to variation in slopes and intercepts between vegetation types not because of bias in individual Ellenberg values but because of prescribed bias in the distribution of Ellenberg values between syntaxa.”
t0“vegetation”
Claim · model-written summary
Adding vegetation type reduces residual variation in calibration.
Verbatim
e0“The residual variation in calibrations carried out across vegetation types is undoubtedly reduced by introducing vegetation type as a factor.”
t0“vegetation”